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Matthew Connor So Zahra Abdallah Jia Hui Du

Abstract

Introduction: Alzheimer’s disease is a type of dementia characterized by a buildup of ꞵ-amyloid plaques and neurofibrillary tangles. Prior to the development of Alzheimer’s disease, patients may experience mild cognitive impairment, characterized by a decline in cognitive abilities while maintaining independent function. Electroencephalography has shown promise as a clinical predictor of mild cognitive impairment. The purpose of this study is to review the existing literature on clinical biomarkers using resting-state electroencephalography or event-related potentials to differentiate Alzheimer’s disease or mild cognitive impairment from normal aging.


Methods: A search of primary research articles was conducted in PubMed. Selected articles examined mild cognitive impairment and Alzheimer’s disease utilising electroencephalography, event-related potential data, and resting-state data. Reviews, conference abstracts, and studies without human controls were excluded.


Results: Our search identified 100 and 125 records on resting-state and event-related potential data, respectively. The most common findings from resting-state studies included a reduction in alpha power, an increase in delta and theta power, a reduction in signal complexity, and differences in functional connectivity. The most common findings from event-related potential studies included reduction in P3 wave amplitude, as well as latency in both P3 and N2 waves.


Discussion: Resting-state and event-related potential electroencephalography studies indicate distinct changes in oscillatory brain activity and waveform shape which indicate distinct differences in MCI or AD compared to HC which may be clinically relevant.


Conclusion: There is evidence to support the use of certain electroencephalographic biomarkers for the diagnosis of Alzheimer’s disease or mild cognitive impairment. Future research should seek to examine how best to apply these findings in a clinical setting.





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Section
Review